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Marketing.

Post Graduate.

Rajiv Bapna and Pradeep Bapna co-founded Allied Electronics & Magnetics Limited (widely known as Amkette) in the year 1985 for the production of floppy diskettes in India. By the year 1995, Amkette was the largest selling floppy diskette brand in India. With the advent of new technology in storage media sale of floppy diskette observed a constant decline. By the end of year 2004, floppy diskettes completely vanished from the market. Amkette anticipated the changes in the computer peripherals market and introduced a wide range of products in storage media, wireless and wired peripherals, accessories and digital lifestyle products. After the launch of Evo TV on June 2012, Amkette was hopeful for a major success in digital lifestyle segment. Evo TV, a connected TV device, allowed consumers to use smart apps on their television sets and was a cost-effective substitute to Smart TVs. Amkette was betting very high on Evo TV for revenue generation and market development.

Following are the learning outcomes: to review the product life cycle of technology products, to understand evolving customers’ expectations and behavior, to assess the adoption process of innovative products and to explore the challenges associated with innovative products for market development.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 8: Marketing.

The current challenges international charities face with regards to their deteriorating image, as a result of recent scandals (e.g. Oxfam, Save the Children), provide the impetus for this exploratory research, where the purpose of this paper is to examine the conceptualization and dimensionality of non-profit brand image across national cultures.

The study employs a quantitative research design, using multi-country samples from India, Bosnia and Herzegovina and the UK. The authors first examine the psychometric properties of the non-profit brand image scale via confirmatory factor analysis across countries, identifying the optimal model for invariance testing. Further, the authors use multi-group invariance analysis to evaluate whether non-profit brand image (using an 18-item scale and six factors) provides equivalent measurement across cultures.

The study shows that individuals in the three countries perceive non-profit brand image equally, and as consisting of perceptions of usefulness, efficiency, affect, dynamism, reliability and ethicality. However, the results also indicate that the means of the dimensions of non-profit brand image are not comparable across different cultures.

The study extends limited current literature on non-profit brand image in international contexts, deriving insightful suggestions for further theoretical approaches in this under-developed research domain. It also yields key implications for charities and other non-profit organizations operating internationally, as they can use non-profit brand image and its dimensions as actionable tools in their communication campaigns to shape their brand image.

The purpose of this paper is to present different naming, packaging, and pricing strategies adopted by private label (PL) retailers in India. This study also aims to identify preferred private label brand (PLB) categories, factors influencing their selection, and the importance of cues in evaluation of PLBs. The overall purpose is to identify important areas for future research of PLBs in the wake of organized retail growth in an emerging economy (India is the context here).

This study is based on in-store observations of major Indian retail chains, longitudinal analyses of customers’ shopping bills, qualitative analyses of consumer interviews, and focus group discussions.

The results indicate that retailers primarily adopt “Sub-branding” (using the store name along with a separate brand name) and “House of Brands” (using a separate brand name only) strategies to sell PLBs in the Indian market. Groceries, food and beverages, and apparel are the preferred categories in PLB. Price, quality, and convenience are the major factors influencing PLB. Taste, ingredients, packaging, price, brand name, and store name are the main factors that are used to evaluate PLBs.

Due to the qualitative analyses and interpretation, there are limitations to this study which need to be empirically validated.

This research has implications for organized retailers in understanding the various strategies used for PLBs in India.

This study is a novel study for documenting the PLB strategies adopted by organized retailers in India. It also uses a longitudinal exploratory approach to further understanding the consumption of PLBs in India.

In spinning industries, selection of the most appropriate fibre for yarn manufacturing plays an important role for achieving an optimal mix of several yarn characteristics, like maximum tenacity, elasticity and spinning ability; and minimum unevenness and hairiness. Identification of the best suited cotton fibre from a set of available alternatives in presence of different conflicting physical properties is often treated as a multi-criteria decision-making (MCDM) problem. The paper aims to discuss this issue.

In this paper, the preference ranking organisation method for enrichment of evaluations (PROMETHEE) and geometrical analysis for interactive aid (GAIA) methods are integrated to solve a cotton fibre selection problem. The PROMETHEE II method ranks the alternative cotton fibres based on their net outranking flows, whereas GAIA acts as a visual aid to strongly support the derived selection decision. The weight stability intervals for all the considered fibre properties (criteria) over which the position of the top-ranked cotton fibre remains unchanged are also determined.

The clusters of cotton fibres formed in the developed GAIA plane act as a yard stick for their appropriate grading to aid the blending process. The ranking of 17 cotton fibres as achieved applying the combined PROMETHEE-GAIA approach highly corroborates with the observations of the past researchers which proves its immense potentiality and applicability in solving fibre selection problems.

Two MCDM methods in the form of PROMETHEE II and GAIA are integrated to provide a holistic approach for cotton fibre grading and selection while taking into consideration all the available cotton fibre properties.

Technical education plays an important role in the development of a country in this age of knowledge economy. Indian technical education system is facing many opportunities and challenges, one of which is how to assess the performance of technical institutions based on multiple criteria. The purpose of this paper is to describe and illustrate an application of a structured approach to determine relative efficiency and ranking of a set of private engineering colleges under multi-criteria environment.

To cater to the increasing need of technical manpower, a very large number of private engineering colleges have been established in the state of West Bengal of eastern India within a very short period. Uniform and acceptable quality of the graduates from many of these private engineering colleges is a concern today and therefore the need for performance evaluation and ranking of these colleges is paramount. For the proposed framework a comparatively new multiple criteria decision-making tool, multiple objective optimization on the basis of simple ratio analysis (MOOSRA) is applied for performance evaluation of eight private engineering colleges taking into account some selected criteria. The subjective weights of the criteria are determined using fuzzy analytic hierarchy process (AHP).

For the analysis, the required data have been provided by the management of the colleges for the academic year of 2011-2012. Based on request of the management identities of these institutes are not disclosed. The institutes are considered as anonymous institute and coded as A, B, C, D, E, F, G and H, respectively. The result of the study reveals that E is the best and the ranking the authors get is in the order of E > F > A > H > D > C > G > B. The result shows that composite performance scores of institutions A, E and F are above the mean performance score value. Therefore these three institutions can be considered as the benchmark or peer group for the remaining five institutions which lie below the mean line of the performance score value.

This paper provides a comprehensive yet detailed methodology for performance evaluation of academic institutions. The novelty in the approach is that fuzzy AHP and MOOSRA are being used as a benchmarking technique in a simple methodology which is generic in nature. It is one of the few studies that evaluate the performance of technical institutions in India.

Managers prefer semantic imbeds in brand names, but extant literature has primarily studied fictitious names for their sound-symbolic perceptions. This paper aims to explore sound-symbolic perceptions of products with blended brand names (BBNs), formed with at least one semantic and one nonsemantic component. Unlike most extant literature, this study not only estimates the effect of vowels and consonants individually on product perceptions but also of their combinations. The boundary condition for this effect is examined by classifying products by their categorization and attributes by their abstractness.

Through a within-subject experiment, this paper tested perceptions of products with BBNs having high-/low-frequency sounds. A mixed-design experiment followed with sound frequency, product-level categorization and attributes’ abstractness as predictor variables.

For BBNs, vowel sounds convey brand meaning better than the combinations of vowel and consonant sounds – and these convey brand meaning better than consonant sounds. Differences in consumers’ perceptions of products with BBNs occur when the degree of attributes’ abstractness matches product-level categorization, such as when concrete attributes match subordinate-level categorization.

Brand managers/strategists can communicate product positioning (attribute-based) through BBNs created specifically for product categories and product types.

This research presents a comparative analysis across vowels, consonants and their combinations on consumers’ perceptions of products with BBNs. Manipulation of names’ length and position of the sound-symbolic imbed in the BBN proffered additional contributions. Another novelty is the interaction effect of product categorization levels and attributes’ abstractness on sound-symbolic perception.

This study aims to investigate the influence of Big Five Personality traits (i.e. openness to experience, conscientiousness, extraversion, agreeableness and neuroticism) on young consumers’ intentions to share branded viral video advertisements. Further, this study also demonstrates that the advertising appeal (informational versus emotional) used in the viral advertisement moderates the effects of specific personality traits on the sharing of viral ads.

A conceptual framework is proposed based on the Five-Factor Model of Personality (McCrae and John, 1992) and advertising effectiveness literature. Using experiments, responses from young consumers were collected and hypotheses were tested using hierarchical regression and ANOVA.

Results reveal that the two personality traits, extraversion and openness to experiences, are positively associated with consumers’ viral ad sharing intentions, whereas conscientiousness, agreeableness and neuroticism are not. Moreover, individuals scoring high on openness and extraversion prefer sharing branded viral ads containing informational appeal vis-ã-vis those containing emotional appeals.

Studies decoding the factors behind the success of viral advertisements have more often focussed on the ad content rather than on personality dimensions of the ad sharers. This study bridges this gap by investigating the influence of Big Five Personality traits on young consumers’ intention to forward viral ads, in interaction with ad appeal. Young consumers represent key audience segments consuming and sharing viral content online, and hence, it is important to have a deeper understanding of this market segment.

Extant research on comparative advertising has focused only on “market leader” comparisons (a brand targeting the market leader), whereas in the marketplace, “multi-brand” comparisons are more prevalent (Kalro et al., 2010). Moreover, most research focuses on direct comparisons only. Hence, this research aims to investigate the interplay between comparison ad strategy (“market leader”/“multi-brand” comparisons) and comparison ad format (direct/indirect comparisons) on the effectiveness of comparative advertising.

This paper uses four 2 × 2 fully crossed factorial designs (comparison ad format: direct vs indirect and comparison ad strategy: market leader vs multi brand) with established and new brands in two categories: powdered detergents and smart phones. All studies were conducted in metropolitan cities of India.

By and large, the experiments indicated that direct (indirect) comparisons lowered (heightened) perceived manipulative intent and enhanced (reduced) attitude-toward-the-ad for multi-brand (market leader) comparisons.

Findings suggest that when advertisers use comparative advertising, they may use direct ads when using multi-brand comparisons and use indirect ones when using market leader comparisons. It could also be argued that when advertisers use multi-brand comparisons because of fragmentation in the marketplace, they may directly compare against these multiple brands. When advertisers need to compare against a market leader, they may do so indirectly.

This research is among the first to investigate multi-brand comparisons that are widely used in the industry and that too in the context of both direct and indirect comparison formats.

Due to liberalization, privatization and globalization, the need of competent technical manpower at an economical cost is increasing rapidly. Many foreign multinationals are focusing on India for employable talents. Many technical institutions with cutting edge technologies and leading edge techniques are being set up by foreign collaboration, national and private initiatives. The objective of this study is to propose a model for performance evaluation and benchmarking of Indian technical institutions from perspective of all stakeholders.

For the proposed framework, a multiple criteria decision‐making tool, distance‐based approach (DBA) methodology is applied for performance evaluation of seven Indian technical institutions taking into account some selected criteria like, faculty strength (FS), student intake (SI), number of PhD awarded (PhD), number of patents applied for (patent), the campus area in acres (CA) and tuition fee per semester in rupees (TF). Consulting the experts in various fields with the help of certain questionnaire and aggregating their views by conducting ameliorated nominal group technique session, we select these evaluation criteria. The subjective weights of the criteria are determined using analytic hierarchy process (AHP). For the analysis, the required data are collected from annual report published by Ministry of Human Resource and Development (MHRD) for the year of 2007‐08.

In this paper, we have chosen seven centrally funded technical institutions for study and the institutions are coded as A, B, C, D, E, F and G. The result of the study reveals that A is the best and F is the worst. The ranking we get is in the order of A≽B≽E≽C≽G≽D≽F. From the result it is understood that A can be considered as benchmark for B, C and E (which form the second group) and this second group can be considered as an improvement target for the rest. At the end a holistic technical education system model (HTESM) is proposed.

This paper is one of the few studies that evaluate the performance of technical institutions in India. The novelty in the approach is that DBA and AHP are being used as a benchmarking technique in a simple methodology which is generic in nature.

The purpose of this paper is to deal with a new generalized model of thermoelasticity theory with memory-dependent derivatives (MDD).

The two-dimensional equations of generalized thermoelasticity with MDD are solved using a state-space approach. The numerical inversion method is employed for the inversion of Laplace and Fourier transforms.

The solutions are presented graphically for different values of time delay and kernel function.

The governing coupled equations of the new generalized thermoelasticity with time delay and kernel function, which can be chosen freely according to the necessity of applications, are applied to a two-dimensional problem of an isotropic plate.